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Bio
His research interest is in the field of machine learning, deep learning and data analysis covering a wide range of theory and numerous scientific (Physics, Chemistry and Neuroscience) and industrial applications. GS > 69000, h 114. His research areas include statistical learning theory for neural networks, support vector machines and ensemble learning techniques. He contributed to the field of signal processing working on time-series analysis, statistical denoising methods and blind source separation. His present application interests are expanded to the analysis of biomedical data, most recently to brain computer interfacing, genomic data analysis, computational chemistry and atomistic simulations.
Research Interests
Papers共 642 篇Author StatisticsCo-AuthorSimilar Experts
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SCIENCE ADVANCESno. 14 (2024): eadn4397-eadn4397
arxiv(2024)
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ENERGY AND AI (2024): 100328
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCEno. 5 (2024): 3257-3274
PATHOLOGIEno. 2 (2024): 133-139
arxiv(2024)
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Julius Hense,Mina Jamshidi Idaji,Oliver Eberle,Thomas Schnake,Jonas Dippel, Laure Ciernik,Oliver Buchstab,Andreas Mock,Frederick Klauschen,Klaus-Robert Müller
CoRR (2024)
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ANNUAL REVIEW OF PATHOLOGY-MECHANISMS OF DISEASEno. 1 (2024): 541-570
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Author Statistics
#Papers: 585
#Citation: 86302
H-Index: 118
G-Index: 289
Sociability: 7
Diversity: 3
Activity: 345
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